More and more systems, whether these are security systems or road charging systems, rely on the taking of photographs in order to identify people or vehicles. In order to identify people or vehicles, information is extracted from the photograph, such as a vehicle registration number or an employee number. Often the photograph is taken while people or vehicles are on the move and in all kinds of weather conditions.
When relying on these photographs for identification or data extraction purposes, the quality of the photographs plays a vital part. Often the weather obscures the photographs. For example, one day the weather may be sunny and bright and although this would seem like good weather conditions for taking a photograph, the sun may reflect on the vehicle's paint work and cause a certain amount of glare, thus causing distortion of the photograph. On another day the weather may be snowing and thus a clear image cannot be taken because the snow may be adhering to the vehicle, thus obscuring the vehicle registration number. Other variables may comprise the quality of daylight or whether the charging point's light source is capable of providing an adequate light source in which to illuminate the license plate at night, or how fast the vehicle is traveling through a charging point area, or even the vehicle's height and size, etc.
In order to make any meaningful sense of data contained within a photograph, optical character recognition (OCR) engines are deployed to translate characters within the image into a standard encoding scheme. Due to the fact that some photographs (for example, a photograph of a vehicle license plate) may be obscured because of snow resting on the license plate, the OCR engine may not be able to confidently translate the image characters into the appropriate encoding scheme. It has been shown in the art that the OCR translation results are far from accurate. This poses a problem in vehicle charging environments where actions such as billing the vehicle owner are carried out on the basis of the OCR results which are often not accurate.
Thus there is a need in the art for a means to verify and improve on the OCR translation results.